Upgrading your skills constantly is the way to stay on the top.
What skills do you need to have to become a Data Scientist?
I have written before but I’ll try to put again some more info to help the people who really want to go that path.
Free Tools can help a lot to start!
There are many tools that can help you overcome this easily to some extent: KNIME is one great tool I use literally every day. It is really easy to learn and it covers 90% of the tasks you will be asked daily as Data Scientist. The best is free.
Check it out here: https://www.knime.org/
Other similar tools: RapidMiner
The important fact is you should know what to do with it.
I have given numerous courses on how they use the tool and how to start with super basic DS tasks.
Understanding Basic terms can help you along the way:
What are regression and what classification?
It is good to know how to approach a specific problem in order to solve it. Almost every problem in the world we are trying to solve can fall into these two.
What algorithms can be used and should be used for each problem?
This is important but not show stopper for the beginning. Decision trees can do just right for a start.
How to do:
Data Cleaning or Transformation
This is one of the most important things you’d come across working in Data Science. 90% of the time, you are not going to get well-formatted data. If you are skilled in one of the programming language, Python or R, you should be pro at packages like Pandas or Dplyr/Reshape.
Exploratory Data Analysis
Once again, this is the most important part, whether you are working to take insights or you want to do predictive modeling, this step comes in. You must train your mind analytically to make an image of variables in your head. You can build such a mind by practice. After that, you must be very good with hands-on with packages like matplotlib or ggplot2, depending upon the language you work with
Machine Learning / Predictive Modelling
One of the most important aspects of today’s data science is predictive modeling. This is dependent upon your EDA and your knowledge of mathematics. I must inform you that invest your time in theory. The more theoretical knowledge you have, the better you’d be going to do. There is no easy way around it. There’s this great course by Andrew NG that goes much into theory. Take it.
If you want to go more advanced, it is important to have a grip on at least one programming language widely used in Data Science. But you should know a little of another language. Either you should know R very well and some Python or Python very well but some R.
Example of complete data analysis that one Data Scientist is doing can be found here.
I use Knime, R and Python every day, I think if you are a total beginner, its good idea to start with KNIME.
Useful courses for learning Data Scientists
I really recommend spending some time on the following courses:
I have passed them myself and I learned a lot from each of it.
Image credit: House of bots